| 31. |
- Abdollahi, Mehdi, 1985, et al.
(författare)
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Dynamic rheological, microstructural and physicochemical properties of blend fish protein recovered from kilka (Clupeonella cultriventris) and silver carp (Hypophthalmichthys molitrix) by the pH-shift process or washing-based technology
- 2017
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Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 229, s. 695-709
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Tidskriftsartikel (refereegranskat)abstract
- This study aimed to evaluate how blending pH-shift produced protein isolates from gutted kilka (Clupeonella cultriventris) and silver carp (Hypophthalmichthys molitrix) affected dynamic rheological and chemical properties of the proteins as well as microstructural and physico-mechanical properties of produced gels. Studied variables were protein solubilization pH (acid vs. alkaline) and blending step (before or after protein precipitation). Comparisons were made with conventionally washed minces from kilka and silver carp fillets; either alone or after blending. Rheological studies revealed that blending alkali-produced protein isolates before precipitation resulted in rapid increase of G′ reflecting the formation of intermolecular protein-protein interactions with higher rate. Furthermore, blending of alkali-produced protein isolates and washed minces, respectively, of kilka and silver carp improved physico-mechanical properties of the resultant gels compared to pure kilka proteins. However, the pH-shift method showed higher efficacy in development of blend surimi at the same blending ratio compared to the conventional washing.
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| 32. |
- Abdollahi, Mehdi, 1985, et al.
(författare)
-
Effect of stabilization method and freeze/thaw-aided precipitation on structural and functional properties of proteins recovered from brown seaweed (Saccharina latissima)
- 2019
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Ingår i: Food Hydrocolloids. - : Elsevier BV. - 0268-005X. ; 96, s. 140-150
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Tidskriftsartikel (refereegranskat)abstract
- - Structural, functional and nutritional properties of protein recovered from brown seaweed, S. latissima with alkaline solubilization/isoelectric precipitation as a function of different post-harvest stabilization methods were studied. The latter included freezing at −20 °C/-80 °C, oven-drying, sun-drying, freeze-drying and ensilaging. Also, the efficacy of freeze/thaw-aided precipitation (F/T) in improving protein recovery of the process was evaluated. The freeze-dried, oven-dried, and −20 °C frozen seaweeds resulted in significantly higher protein yield than the −80°C-frozen, sun-dried and ensiled biomasses. F/T increased protein precipitation and doubled total protein yield. Sun-drying and −20°C-freezing caused extensive protein degradation as revealed by SDS-PAGE and HP-SEC, while oven-drying altered the seaweed protein structure with less α-helices. Functional properties of the seaweed proteins were remarkably affected by stabilization condition and F/T, but nutritional value of the proteins was only dependent on stabilization method. Thus, to efficiently recover seaweed proteins, its post-harvest stabilization condition must be carefully chosen based on the final application of the proteins. © 2019 The Authors
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| 33. |
- Abdollahi, Mehdi, 1985, et al.
(författare)
-
Minimizing lipid oxidation during pH-shift processing of fish by-products by cross-processing with lingonberry press cake, shrimp shells or brown seaweed
- 2020
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Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 327
-
Tidskriftsartikel (refereegranskat)abstract
- The potential of cross-processing herring or salmon by-products with brown seaweed, shrimp peeling by-products and lingonberry press cake (called “helpers”) to minimize lipid oxidation during acid/alkaline pH-shift protein isolation was evaluated. Lingonberry press cake remarkably reduced levels of lipid hydroperoxides, malondialdehyde (MDA) and 4-hydroxy-trans2-hexenal (HHE) in both herring and salmon protein isolates (PI) while seaweed and shrimp by-product mitigated generation of MDA and HHE in herring PI. The salmon PI, however, by itself had very low oxidation levels. Cross-processing reduced protein yield compared with the classical pH-shift process by diminishing protein solubility, but still, the alkaline process version was promising. The color of the PIs varied greatly between different process combinations, reflecting partitioning of natural pigments into isolates. Altogether, cross-processing seems a promising tool for inhibition of lipid oxidation during pH-shift processing of sensitive fish by-products, with the alkaline version and lingonberry press cake being closest at hand for further studies.
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| 34. |
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| 35. |
- Abdollahi, Mehdi, 1985, et al.
(författare)
-
Tuning the pH-shift protein-isolation method for maximum hemoglobin-removal from blood rich fish muscle
- 2016
-
Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 212, s. 213-224
-
Tidskriftsartikel (refereegranskat)abstract
- A main challenge preventing optimal use of protein isolated from unconventional raw materials (e.g., small pelagic fish and fish by-products) using the pH-shift method is the difficulty to remove enough heme-pigments. Here, the distribution of hemoglobin (Hb) in the different fractions formed during pH-shift processing was studied using Hb-fortified cod mince. Process modifications, additives and prewashing were then investigated to further facilitate Hb-removal. The alkaline pH-shift process version could remove considerably more Hb (77%) compared to the acidic version (37%) when proteins were precipitated at pH 5.5; most Hb was removed during dewatering. Protein precipitation at pH 6.5 improved total Hb removal up to 91% and 74% during alkaline and acid processing, respectively. Adding phytic acid to the first supernatant of the alkaline process version yielded 93% Hb removal. Combining one prewash with phytic acid at pH 5.5 followed by alkaline/acid pH-shift processing increased Hb removal up to 96/92%.
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| 36. |
- Abdulgadir, Alamin, et al.
(författare)
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Performance Simulation of a Composite Filter Material Containing Mechanical Pulp Fibers, Microfibrillated Cellulose, and Cellulose Nanofibers
- 2022
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Ingår i: Proceedings of the International Mechanical Pulping Conference. ; , s. 160-
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Nonwoven fibrous materials with reticular support of an interconnected fiber network and a tortuous airflow pathway have been commonly used in filtration applications. To meet the criteria of filter efficiency and performance, the filter materials are recommended to contain different types of fibers such as mechanical pulp fibers, microfibrillated cellulose, cellulose nanofibers, and other polymer or synthetic fibers with a range of dimensions, i.e., length and diameter. Cellulose fibers in filter media possess irregular and complex structures with hollow or collapsed lumen structures owing to their refinement or pulping method. The development of an appropriate filter media model requires information on actual fiber characteristics. In this study, a simulation method was used to investigate the complex microstructures of filter media. The physical parameters such as fiber wall thickness, diameter, length, cross-section shapes, and curliness were obtained from fiber analyzers and scanning electron microscopy. Based on the experimental findings, GeoDict database comprising different types of common fiber models was constructed. 3-Dimensional fibrous models corresponding to the wet-laid binderless filter material were generated. Using the GeoDict modules, the pore size distributions, average pore sizes, air permeability, pressure drop and initial filter efficiency simulations were performed. The simulation results appear to be in close agreement with the experimental results. The incorporation of cellulose nanofibers resulted in reduced average pore sizes and air permeability of the filter material, thus enhancing the initial filter efficiency. The filter media developed a biobased material derived from pulp fibers for advanced applications such as medical facemask, and air filtration purposes.
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| 37. |
- Abebe, Admas Alemu, et al.
(författare)
-
Genome-Wide Association Analysis and Genomic Prediction for Adult-Plant Resistance to Septoria Tritici Blotch and Powdery Mildew in Winter Wheat
- 2021
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Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53-0.75 and 0.36-0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines.
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| 38. |
- Abebe, Admas Alemu
(författare)
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Genome-wide association study for yield-related traits in sesame (Sesamum Indicum)
- 2022
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Ingår i: Plant Breeding. - : Wiley. - 0179-9541 .- 1439-0523. ; 141, s. 246-256
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Tidskriftsartikel (refereegranskat)abstract
- Sesame is an important oil crop in Ethiopia and other regions in terms of both area coverage and production. However, productivity is low due to biotic and abiotic stresses. Therefore, dissecting the genetic basis of quantitatively inherited yield-related traits is instrumental to developing stable and high-yielding varieties. A genome-wide association study (GWAS) was performed with a diverse set of 300 sesame accessions tested in two environments and 2997 SNP markers. In total, 21 significant marker-trait associations (MTAs) were detected for seven yield-related traits, including days to flower initiation (DFI), days to 50% flowering (DF), days to physiological maturity (DM), capsule length (CAPL), seeds per capsule (SPC), 1000-seed weight (TSW) and bacterial blight (BBL). The majority of MTAs detected on LG 3, 7 and 8 were associated with traits related to physiological periods. Dissecting genetic control of flowering time and maturity has a pivotal contribution to fostering sesame breeding and developing new varieties adaptable to changing climatic conditions. Our GWAS results will assist in incorporating alleles into the elite sesame germplasm through marker-assisted selection.
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| 39. |
- Abebe, Admas Alemu, et al.
(författare)
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Genomic selection in plant breeding: key factors shaping two decades of progress
- 2024
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Ingår i: Molecular Plant. - 1674-2052 .- 1752-9867. ; 17, s. 552-578
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Forskningsöversikt (refereegranskat)abstract
- Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP—theoretically reaching one when using the Pearson’s correlation as a metric—is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding.
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| 40. |
- Abebe, Admas Alemu, et al.
(författare)
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Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
- 2023
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Ingår i: TAG Theoretical and Applied Genetics. - 0040-5752 .- 1432-2242. ; 136
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Tidskriftsartikel (refereegranskat)abstract
- Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r2 < 0.5), while stringent LD was required for spike length (SPL) and flag leaf area (FLA). Trait-linked SNPs identified only from training populations failed to improve the prediction accuracy of the four studied traits. Pre-selection of SNPs via LD-based haplotype-tagging could play a vital role in optimizing genomic selection and reducing genotyping costs. Furthermore, the method could pave the way for developing low-cost genotyping methods through customized genotyping platforms targeting key SNP markers tagged to essential haplotype blocks.
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